2.3k citations · 3.1k across the 15 of their papers we have counts for
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S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces
Eric Nguyen, Karan Goel, Albert Gu +5
Visual data such as images and videos are typically modeled as discretizations of inherently continuous, multidimensional signals. Existing continuous-signal models attempt to expl…
Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding
William Chen, Siyi Hu, Rajat Talak +1
Abstract semantic 3D scene understanding is a problem of critical importance in robotics. As robots still lack the common-sense knowledge about household objects and locations of a…
On the Parameterization and Initialization of Diagonal State Space Models
Albert Gu, Ankit Gupta, Karan Goel +1
State space models (SSM) have recently been shown to be very effective as a deep learning layer as a promising alternative to sequence models such as RNNs, CNNs, or Transformers. T…
It's Raw! Audio Generation with State-Space Models
Karan Goel, Albert Gu, Chris Donahue +1
Developing architectures suitable for modeling raw audio is a challenging problem due to the high sampling rates of audio waveforms. Standard sequence modeling approaches like RNNs…